docs: add AutoGen integration cookbook by manojkulkarni123 · Pull Request #88 · usemoss/moss

manojkulkarni123 · 2026-03-29T16:27:38Z

Pull Request Checklist

I have read the CONTRIBUTING guide.
I have updated the documentation (if applicable).
My code follows the style guidelines of this project.
I have performed a self-review of my own code.
I have added tests that prove my fix is effective or that my feature works.
New and existing unit tests pass locally with my changes.

Description

This PR adds a comprehensive cookbook example demonstrating how to use Moss as a sub-10ms retrieval tool for AutoGen multi-agent conversations, fulfilling the requirements of the linked issue.

Deliverables Addressed:

docs/examples/autogen.md: Created a full working example in Markdown format as requested.
Tested end-to-end with current AutoGen version: The example was built and verified end-to-end using the latest AutoGen v0.4.x (autogen-agentchat) API, utilizing AssistantAgent instead of the older ConversableAgent mentioned in the original issue description. This aligns the cookbook with AutoGen's current recommended patterns and ensures the documentation remains relevant.

Additional Value:

Runnable Notebook: In addition to the requested markdown guide, I have included a runnable Jupyter notebook (moss_autogen.ipynb) to match the repository's established style for cookbooks.

Files Added:

docs/examples/autogen.md
examples/cookbook/autogen/moss_autogen.ipynb

Fixes #80

Type of Change

Bug fix (non-breaking change which fixes an issue)
New feature (non-breaking change which adds functionality)
Breaking change (fix or feature that would cause existing functionality to not work as expected)
This change requires a documentation update

vercel · 2026-03-29T16:27:44Z

@manojkulkarni123 is attempting to deploy a commit to the Moss Team Team on Vercel.

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CLAassistant · 2026-03-29T16:27:45Z

All committers have signed the CLA.

yatharthk2 · 2026-04-01T23:02:23Z

Thanks for the Pr @manojkulkarni123 , I have reviewed and added comments.

…feat/autogen-cookbook

manojkulkarni123 · 2026-04-03T18:34:43Z

Hey @yatharthk2 , thank you for the feedback! I have updated the PR to address all of your review comments:

Relocated & Renamed Docs: Moved the documentation into the cookbook directory and renamed it to README.md.
Switched to uv: Updated the installation instructions in both the README and Jupyter Notebook to use uv instead of
standard pip.
Added .env.example
Upgraded to a Multi-Agent E-Commerce System: Scaled up from a simple FAQ agent to a complete multi-agent support
team. It features 3 specialized agents (product, shipping, and returns) each equipped with its own isolated Moss index
and themed dataset collaborating dynamically.
Added Exact Latency Benchmarking: Built an InstrumentedMossSearch wrapper that automatically injects real-time
latency tool logs into the AutoGen stream (e.g., [MOSS] product_search | latency: 1189ms) and prints a final aggregated
summary

Let me know if this looks good to you!

yatharthk2 · 2026-04-05T01:47:43Z

+    "        start_time = time.perf_counter()\n",
+    "        opts = QueryOptions(top_k=top_k)\n",
+    "        results = await self.moss.query(index_name, query, opts)\n",
+    "        end_time = time.perf_counter()\n",


Moss search result type provides the calculated time for query, please feel free to refer below. Might reduce the code complexity of the notebook.

https://docs.moss.dev/docs/reference/js/interfaces/SearchResult

yatharthk2 · 2026-04-05T02:17:26Z

+    "\n",
+    "    await load_index(\"product_catalog.json\", \"product_catalog_index\")\n",
+    "    await load_index(\"shipping_policies.json\", \"shipping_policies_index\")\n",
+    "    await load_index(\"return_policies.json\", \"returns_index\")\n",


load_index is just create_index in disguise and all your queries are going to moss cloud, this is also the reason you are seeing higher latency. Please feel free to refer the python docs at https://docs.moss.dev/docs/reference/js/classes/MossClient

to check the loadIndex() definition and can you please use local searching ?

That'll definitely reduce code complexity, will use SearchResult timeTakenInMs

And yes, the load_index is create_index in disguise my bad, Will use loadIndex() directly to enable local search, which should significantly reduce latency.

yatharthk2 · 2026-04-08T22:45:47Z

is this stil being worked upon, should I close it ?

manojkulkarni123 · 2026-04-09T03:47:18Z

Hey @yatharthk2 ill submit a pr soon sorry was caught up with some work

…ub-millisecond (< 10ms) retrieval inside multi-agent orchestration loops. - Replaced manual perf_counter wrappers with Moss's native SearchResult.time_taken_ms property for elegant latency tracking. - Expanded the JSON datasets (Product, Shipping, Returns) with more data points.

devin-ai-integration

Devin Review found 1 new potential issue.

View 3 additional findings in Devin Review.

devin-ai-integration · 2026-04-09T06:25:30Z

🚩 No tests included, unlike the langchain cookbook example

The langchain cookbook at examples/cookbook/langchain/ includes a test_integration.py with unit tests and a pyproject.toml. This autogen example has no tests. CONTRIBUTING.md states "If you've added code that should be tested, add tests." However, the dspy example (examples/cookbook/dspy/) also has no tests, so this is consistent with at least one existing pattern. For a notebook-only cookbook, the lack of tests is arguably acceptable, but adding at least mock-based tests for the tool functions (like the langchain example does) would improve reliability.

Was this helpful? React with 👍 or 👎 to provide feedback.

manojkulkarni123 · 2026-04-09T06:45:32Z

Hey @yatharthk2, sorry for the delay, was caught up with work!

I've updated the PR based on your review feedback. Here's a summary of the changes:

Used load_index() rather than querying it directly from moss cloud
Updated latency tracking to directly use SearchResult.time_taken_ms and the previous removed redundant code
Updated package name from inferedge-moss to moss
Added more examples to the JSON dataset

Please let me know if there's anything else you'd like me to change.

…ime_taken_ms , unused imports, and latencies list by adding a try finally which will run latencies.clear() preventing stale latency values

yatharthk2 · 2026-04-11T00:05:16Z

+    "async def setup_indices():\n",
+    "    async def create_index_from_file(filename, index_name):\n",
+    "        with open(f\"data/{filename}\", \"r\") as f:\n",
+    "            data = json.load(f)\n",
+    "        docs = []\n",
+    "        for i, item in enumerate(data):\n",
+    "            text_repr = \", \".join([f\"{k}: {v}\" for k, v in item.items()])\n",
+    "            doc_id = item.get(\"id\", f\"doc_{i}\")\n",
+    "            string_metadata = {k: str(v) for k, v in item.items()}\n",


can you please add a check if the index already exits ?

yatharthk2 · 2026-04-11T00:11:22Z

+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    " The `moss_client.load_index()` command is the secret sauce for agent loops. It forces the cloud index into your machine's local RAM. Because agent loops require sequential data retrieval, using a standard cloud database adds 200-500ms of HTTP network overhead sequentially. Local cached execution allows Rust to perform vector dot-products in microseconds, bridging the gap between agent logic and data retrieval."


can you please remove, "Local cached execution allows Rust to perform vector dot-products in microseconds, bridging the gap between agent logic and data retrieval"

yatharthk2 · 2026-04-11T00:29:05Z

Overall looks great,Added 2 small comments to be addressed, will approve after this.

…oved cookbook explanation

manojkulkarni123 · 2026-04-11T03:11:51Z

Hey @yatharthk2, thanks for the review! I've addressed your points:

Added a check for existing indices using list_indexes so the cell can be re run without errors.
Simplified the description of load_index().

if you are satisfied with these changes then please do approve it

yatharthk2

Thanks for the PR, Looking forward to more collabs :)

manojkulkarni123 · 2026-04-11T03:53:10Z

Hey @yatharthk2 thank you for being so patient with me
Will keep contributing to moss 🚀

## Pull Request Checklist - [x] I have read the [CONTRIBUTING](CONTRIBUTING.md) guide. - [x] I have updated the documentation (if applicable). - [x] My code follows the style guidelines of this project. - [x] I have performed a self-review of my own code. - [ ] I have added tests that prove my fix is effective or that my feature works. - [ ] New and existing unit tests pass locally with my changes. ## Description This PR adds a comprehensive cookbook example demonstrating how to use Moss as a sub-10ms retrieval tool for AutoGen multi-agent conversations, fulfilling the requirements of the linked issue. ### Deliverables Addressed: - **`docs/examples/autogen.md`**: Created a full working example in Markdown format as requested. - **Tested end-to-end with current AutoGen version**: The example was built and verified end-to-end using the latest **AutoGen v0.4.x** (`autogen-agentchat`) API, utilizing `AssistantAgent` instead of the older `ConversableAgent` mentioned in the original issue description. This aligns the cookbook with AutoGen's current recommended patterns and ensures the documentation remains relevant. ### Additional Value: - **Runnable Notebook**: In addition to the requested markdown guide, I have included a runnable Jupyter notebook (`moss_autogen.ipynb`) to match the repository's established style for cookbooks. **Files Added:** - `docs/examples/autogen.md` - `examples/cookbook/autogen/moss_autogen.ipynb` Fixes usemoss#80 ## Type of Change - [ ] Bug fix (non-breaking change which fixes an issue) - [ ] New feature (non-breaking change which adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected) - [x] This change requires a documentation update  --- <a href="https://app.devin.ai/review/usemoss/moss/pull/88" target="_blank"> <picture> <source media="(prefers-color-scheme: dark)" srcset="https://static.devin.ai/assets/gh-open-in-devin-review-dark.svg?v=1"> <img src="https://static.devin.ai/assets/gh-open-in-devin-review-light.svg?v=1" alt="Open with Devin"> </picture> </a>

docs: add modern autogen cookbook example

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manojkulkarni123 requested review from CoderOMaster, HarshaNalluru, r4ghu and yatharthk2 as code owners March 29, 2026 16:27

yatharthk2 requested changes Apr 2, 2026

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Merge branch 'main' of https://github.com/manojkulkarni123/moss into …

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…feat/autogen-cookbook

manojkulkarni123 force-pushed the feat/autogen-cookbook branch 2 times, most recently from 87766f7 to 3a1eeae Compare April 3, 2026 18:12

docs(autogen): revise notebook intro and update readme routing flow

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manojkulkarni123 force-pushed the feat/autogen-cookbook branch from d71cd6b to 5739b32 Compare April 3, 2026 18:23

yatharthk2 requested changes Apr 5, 2026

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manojkulkarni123 added 4 commits April 6, 2026 18:54

local changes before merging upstream

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merge conflict fixed

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Merge branch 'main' into feat/autogen-cookbook

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Committing changes before updating latest review changes

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manojkulkarni123 force-pushed the feat/autogen-cookbook branch from c0ec90c to 67890ee Compare April 9, 2026 06:01

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chore: revert accidental file modifications

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resolve Devin PR review lints including None-types for SearchResult.t…

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…ime_taken_ms , unused imports, and latencies list by adding a try finally which will run latencies.clear() preventing stale latency values

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Added team.reset() so next queryruns fully isolated

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yatharthk2 reviewed Apr 11, 2026

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Updated the code to check if the index already exists or not and impr…

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…oved cookbook explanation

yatharthk2 approved these changes Apr 11, 2026

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yatharthk2 merged commit 5677b06 into usemoss:main Apr 11, 2026
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manojkulkarni123 deleted the feat/autogen-cookbook branch April 12, 2026 02:53

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